Efficient Visualization and Reconstruction of 3D Geometric Models from Neuro- Biological Confocal Microscope Scans ; Effiziente Visualisierung und Rekonstruktion von dreidimensionalen geometrischen Modellen aus neurobiologischen konfokalmikroskopischen Scans

Media type: Electronic Thesis; E-Book; Doctoral Thesis

Title: Efficient Visualization and Reconstruction of 3D Geometric Models from Neuro- Biological Confocal Microscope Scans ; Effiziente Visualisierung und Rekonstruktion von dreidimensionalen geometrischen Modellen aus neurobiologischen konfokalmikroskopischen Scans

Contributor: Westerhoff, Malte [Author]

imprint: Freie Universität Berlin: Refubium (FU Berlin), 2004

Language: English

DOI: https://doi.org/10.17169/refubium-4984

Keywords: I.4.6 ; volume rendering ; image segmentation ; P85 ; geometry reconstruction ; 68U05

Origination:

Footnote: Diese Datenquelle enthält auch Bestandsnachweise, die nicht zu einem Volltext führen.

Description: Title, Table of Contents, and Acknowledgements 1 Introduction 1 1.1 Problem Formulation 1 1.2 Motivation 2 1.3 Overview 3 1.4 Outline of the Thesis 3 1.5 Specific Contributions 4 2 Concepts and Techniques 5 2.1 Digital Images 5 2.2 Data Acquisition 7 3 Visualization 10 3.1 Computer Graphics Basics 10 3.2 Image Data Visualization 12 3.2.1 Slicing 13 3.2.2 Color Mapping 14 3.2.3 Maximum Intensity Projection 15 3.2.4 Iso-Surfaces 16 3.2.5 Direct Volume Rendering 18 3.3 Visualizing Graphs and Lines 22 3.3.1 Illumination of Lines in R3 23 3.3.2 Rendering Illuminated Lines 25 3.3.3 Visual Enhancements 27 3.3.4 Results 29 3.4 Enhanced Transparency 29 3.4.1 The Physical Model 30 3.4.2 Implementation 32 3.4.3 Results 35 4 Image Segmentation 37 4.1 Introduction 37 4.2 Interactive Segmentation 39 4.3 Interpolation and Extrapolation 40 4.3.1 Distance Maps 43 4.3.2 Distance Based Interpolation 44 4.3.3 Interpolation for Segmentation 45 4.3.4 Higher Order Interpolation 45 4.3.5 Border Initialization 47 4.3.6 Non-Planar Interpolation 50 4.3.7 Results 50 4.4 Sub-Voxel Accuracy 51 4.5 Results 52 5 Line Extraction 53 5.1 Interactive Extraction 53 5.1.1 Line Extraction in MIP 54 5.1.2 Recovering Depth 58 5.1.3 Results and Discussion 59 5.2 Automatic Extraction 60 5.2.1 Scale Space 61 5.2.2 Line Detection Operators 62 5.2.3 Neuron Data Sets 64 5.2.4 Tree Re-Assembling 64 5.2.5 Skeletonization 65 5.2.6 Radius Estimation 66 5.2.7 Results and Discussion 66 6 Geometry Reconstruction 69 6.1 From Labels to Geometry 69 6.2 Triangulation Algorithm 71 6.2.1 Space Partitioning 71 6.2.2 Cell Triangulation 72 6.2.3 Look-Up Tables 74 6.2.4 Comparison to Marching Cubes 76 6.2.5 Results 76 6.3 Computing Weights 77 6.3.1 Minimal Surfaces 78 6.3.2 Constrained Smoothing 80 6.3.3 Surface Noise 82 6.3.4 Thin Structures 84 6.3.5 Results 85 6.4 From Graphs to Geometry 85 6.4.1 Introduction 85 6.4.2 Algorithm 86 6.4.3 Algorithmic Details and Implementation 87 6.4.4 Results 89 7 Registration and Averaging 90 7.1 Registration 90 7.1.1 Intensity Correlation ...

Access State: Open Access

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